Presupposition in Lexical Analysis and Discourse

This report describes research done at the Artificial Intelligence Laboratory of the Massachusetts Institute of Technology. Support for the laboratory's artificial intelligence research is provided in part by the Advanced Research Projects Agency of the Department of Defense under Office of Naval Research contract N00014-70-A-0362-0003.Recent research in linguistic analysis of presuppositions has provided numerous indications of the role of presupposition in lexical analysis. Still others have argued there is no distinction between meaning and the presupposition of a word. In this paper I discuss both issues of what presuppositions are related to lexical analysis and what happens to these presupposition in discourse. Finally, I comment on how this knowledge could be made available to a natural language understanding program.MIT Artificial Intelligence Laborator

Organizations in a Non-Linear, Unpredictable World

Globalisation, new information technology, universal networking, the nonlinearity of things, and environmental turbulence have changed strategies of managing and succeeding. This paper examines nonlinear phenomena and their practical consequences especially from an organizational perspective by using three concepts: Malcolm Gladwell’s tipping point, Ilya Prigogine’s self-organization, and Algirdas Greimas’s semiotic square. Tipping points occur at all system levels, e.g. such as determining for instance how fashion trends catch on, how health campaigns succeed, and how new ideas spread like wildfire. Self-organization refers to the kind of consciousness, action and intelligence that is manifested in the community’s rather than the individual’s actions, such as swarm intelligence in the animal world. Insight into the dynamics of change is supplemented by the semiotic square, which sheds light on how organizations can succeed. They must have buffers, a surplus of resources to which they can resort whenever something unexpected happens, and they must be attuned to change and have access to tools that promote open, confidence-building communication.Peer reviewe

Current and future multimodal learning analytics data challenges

Multimodal Learning Analytics (MMLA) captures, integrates and analyzes learning traces from different sources in order to obtain a more holistic understanding of the learning process, wherever it happens. MMLA leverages the increasingly widespread availability of diverse sensors, highfrequency data collection technologies and sophisticated machine learning and artificial intelligence techniques. The aim of this workshop is twofold: first, to expose participants to, and develop, different multimodal datasets that reflect how MMLA can bring new insights and opportunities to investigate complex learning processes and environments; second, to collaboratively identify a set of grand challenges for further MMLA research, built upon the foundations of previous workshops on the topic

The Event Calculus Assessed

The range of applicability of the Full Event Calculus is proven to be the Ksp-IA class in the Features and Fluents taxonomy. The proof is given with respect to the original definition of this preference logic, where no adjustments of the language or reasoning method were necessary. The result implies that the claims on the expressiveness and problem-solving power of this logic were indeed correct

Toward Cognitive and Immersive Systems: Experiments in a Cognitive Microworld

As computational power has continued to increase, and sensors have become more accurate, the corresponding advent of systems that are at once cognitive and immersive has arrived. These \textit{cognitive and immersive systems} (CAISs) fall squarely into the intersection of AI with HCI/HRI: such systems interact with and assist the human agents that enter them, in no small part because such systems are infused with AI able to understand and reason about these humans and their knowledge, beliefs, goals, communications, plans, etc. We herein explain our approach to engineering CAISs. We emphasize the capacity of a CAIS to develop and reason over a `theory of the mind' of its human partners. This capacity entails that the AI in question has a sophisticated model of the beliefs, knowledge, goals, desires, emotions, etc.\ of these humans. To accomplish this engineering, a formal framework of very high expressivity is needed. In our case, this framework is a \textit{cognitive event calculus}, a particular kind of quantified multi-operator modal logic, and a matching high-expressivity automated reasoner and planner. To explain, advance, and to a degree validate our approach, we show that a calculus of this type satisfies a set of formal requirements, and can enable a CAIS to understand a psychologically tricky scenario couched in what we call the \textit{cognitive polysolid framework} (CPF). We also formally show that a room that satisfies these requirements can have a useful property we term \emph{expectation of usefulness}. CPF, a sub-class of \textit{cognitive microworlds}, includes machinery able to represent and plan over not merely blocks and actions (such as seen in the primitive `blocks worlds' of old), but also over agents and their mental attitudes about both other agents and inanimate objects.Comment: Submitted to Advances of Cognitive Systems 201

Ethics in AIED: Who cares?

The field of AIED raises far-reaching ethical questions with important implications for students and educators. However, most AIED research, development and deployment has taken place in what is essentially a moral vacuum (for example, what happens if a child is subjected to a biased set of algorithms that impact negatively and incorrectly on their school progress?). Around the world, virtually no research has been undertaken, no guidelines have been provided, no policies have been developed, and no regulations have been enacted to address the specific ethical issues raised by the use of Artificial Intelligence in Education. This workshop, ETHICS in AIED: Who Cares?, is proposed as a first step towards addressing this critical problem for the field. It will be an opportunity for researchers who are exploring ethical issues critical for AIED to share their research, to identify the key ethical issues, and to map out how to address the multiple challenges, towards establishing a basis for meaningful ethical reflection necessary for innovation in the field of AIED. The workshop will be in three parts. It will begin with ETHICS in AIED: What’s the problem?, a round-table discussion introduced and led by Professor Beverly Woolf, one of the world’s most accomplished AIED researchers. This will be followed by Mapping the Landscape, in which up to six AIED conference participants will each give a five-minute ‘lightning’ presentation on ethics in AIED research. The workshop will conclude with Addressing the Challenges, a round-table discussion session in which we will agree on a core list of ethical questions/areas of necessary research for the field of AIED, and will set out to identify next steps